Java Stanford NLP: Part of Speech labels?

Question

The Stanford NLP, demo'd here, gives an output like this:

Colorless/JJ green/JJ ideas/NNS sleep/VBP furiously/RB ./.

What do the Part of Speech tags mean? I am unable to find an official list. Is it Stanford's own system, or are they using universal tags? (What is JJ, for instance?)

Also, when I am iterating through the sentences, looking for nouns, for instance, I end up doing something like checking to see if the tag .contains('N'). This feels pretty weak. Is there a better way to programmatically search for a certain part of speech?

Solution 1

The Penn Treebank Project. Look at the Part-of-speech tagging ps.

JJ is adjective. NNS is noun, plural. VBP is verb present tense. RB is adverb.

That's for english. For chinese, it's the Penn Chinese Treebank. And for german it's the NEGRA corpus.

1. CC Coordinating conjunction
2. CD Cardinal number
3. DT Determiner
4. EX Existential there
5. FW Foreign word
6. IN Preposition or subordinating conjunction
7. JJ Adjective
8. JJR Adjective, comparative
9. JJS Adjective, superlative
10. LS List item marker
11. MD Modal
12. NN Noun, singular or mass
13. NNS Noun, plural
14. NNP Proper noun, singular
15. NNPS Proper noun, plural
16. PDT Predeterminer
17. POS Possessive ending
18. PRP Personal pronoun
19. PRP$ Possessive pronoun
20. RB Adverb
21. RBR Adverb, comparative
22. RBS Adverb, superlative
23. RP Particle
24. SYM Symbol
25. TO to
26. UH Interjection
27. VB Verb, base form
28. VBD Verb, past tense
29. VBG Verb, gerund or present participle
30. VBN Verb, past participle
31. VBP Verb, non­3rd person singular present
32. VBZ Verb, 3rd person singular present
33. WDT Wh­determiner
34. WP Wh­pronoun
35. WP$ Possessive wh­pronoun
36. WRB Wh­adverb

Solution 2

Explanation of each tag from the documentation :

CC: conjunction, coordinating
    & 'n and both but either et for less minus neither nor or plus so
    therefore times v. versus vs. whether yet
CD: numeral, cardinal
    mid-1890 nine-thirty forty-two one-tenth ten million 0.5 one forty-
    seven 1987 twenty '79 zero two 78-degrees eighty-four IX '60s .025
    fifteen 271,124 dozen quintillion DM2,000 ...
DT: determiner
    all an another any both del each either every half la many much nary
    neither no some such that the them these this those
EX: existential there
    there
FW: foreign word
    gemeinschaft hund ich jeux habeas Haementeria Herr K'ang-si vous
    lutihaw alai je jour objets salutaris fille quibusdam pas trop Monte
    terram fiche oui corporis ...
IN: preposition or conjunction, subordinating
    astride among uppon whether out inside pro despite on by throughout
    below within for towards near behind atop around if like until below
    next into if beside ...
JJ: adjective or numeral, ordinal
    third ill-mannered pre-war regrettable oiled calamitous first separable
    ectoplasmic battery-powered participatory fourth still-to-be-named
    multilingual multi-disciplinary ...
JJR: adjective, comparative
    bleaker braver breezier briefer brighter brisker broader bumper busier
    calmer cheaper choosier cleaner clearer closer colder commoner costlier
    cozier creamier crunchier cuter ...
JJS: adjective, superlative
    calmest cheapest choicest classiest cleanest clearest closest commonest
    corniest costliest crassest creepiest crudest cutest darkest deadliest
    dearest deepest densest dinkiest ...
LS: list item marker
    A A. B B. C C. D E F First G H I J K One SP-44001 SP-44002 SP-44005
    SP-44007 Second Third Three Two * a b c d first five four one six three
    two
MD: modal auxiliary
    can cannot could couldn't dare may might must need ought shall should
    shouldn't will would
NN: noun, common, singular or mass
    common-carrier cabbage knuckle-duster Casino afghan shed thermostat
    investment slide humour falloff slick wind hyena override subhumanity
    machinist ...
NNS: noun, common, plural
    undergraduates scotches bric-a-brac products bodyguards facets coasts
    divestitures storehouses designs clubs fragrances averages
    subjectivists apprehensions muses factory-jobs ...
NNP: noun, proper, singular
    Motown Venneboerger Czestochwa Ranzer Conchita Trumplane Christos
    Oceanside Escobar Kreisler Sawyer Cougar Yvette Ervin ODI Darryl CTCA
    Shannon A.K.C. Meltex Liverpool ...
NNPS: noun, proper, plural
    Americans Americas Amharas Amityvilles Amusements Anarcho-Syndicalists
    Andalusians Andes Andruses Angels Animals Anthony Antilles Antiques
    Apache Apaches Apocrypha ...
PDT: pre-determiner
    all both half many quite such sure this
POS: genitive marker
    ' 's
PRP: pronoun, personal
    hers herself him himself hisself it itself me myself one oneself ours
    ourselves ownself self she thee theirs them themselves they thou thy us
PRP$: pronoun, possessive
    her his mine my our ours their thy your
RB: adverb
    occasionally unabatingly maddeningly adventurously professedly
    stirringly prominently technologically magisterially predominately
    swiftly fiscally pitilessly ...
RBR: adverb, comparative
    further gloomier grander graver greater grimmer harder harsher
    healthier heavier higher however larger later leaner lengthier less-
    perfectly lesser lonelier longer louder lower more ...
RBS: adverb, superlative
    best biggest bluntest earliest farthest first furthest hardest
    heartiest highest largest least less most nearest second tightest worst
RP: particle
    aboard about across along apart around aside at away back before behind
    by crop down ever fast for forth from go high i.e. in into just later
    low more off on open out over per pie raising start teeth that through
    under unto up up-pp upon whole with you
SYM: symbol
    % & ' '' ''. ) ). * + ,. < = > @ A[fj] U.S U.S.S.R * ** ***
TO: "to" as preposition or infinitive marker
    to
UH: interjection
    Goodbye Goody Gosh Wow Jeepers Jee-sus Hubba Hey Kee-reist Oops amen
    huh howdy uh dammit whammo shucks heck anyways whodunnit honey golly
    man baby diddle hush sonuvabitch ...
VB: verb, base form
    ask assemble assess assign assume atone attention avoid bake balkanize
    bank begin behold believe bend benefit bevel beware bless boil bomb
    boost brace break bring broil brush build ...
VBD: verb, past tense
    dipped pleaded swiped regummed soaked tidied convened halted registered
    cushioned exacted snubbed strode aimed adopted belied figgered
    speculated wore appreciated contemplated ...
VBG: verb, present participle or gerund
    telegraphing stirring focusing angering judging stalling lactating
    hankerin' alleging veering capping approaching traveling besieging
    encrypting interrupting erasing wincing ...
VBN: verb, past participle
    multihulled dilapidated aerosolized chaired languished panelized used
    experimented flourished imitated reunifed factored condensed sheared
    unsettled primed dubbed desired ...
VBP: verb, present tense, not 3rd person singular
    predominate wrap resort sue twist spill cure lengthen brush terminate
    appear tend stray glisten obtain comprise detest tease attract
    emphasize mold postpone sever return wag ...
VBZ: verb, present tense, 3rd person singular
    bases reconstructs marks mixes displeases seals carps weaves snatches
    slumps stretches authorizes smolders pictures emerges stockpiles
    seduces fizzes uses bolsters slaps speaks pleads ...
WDT: WH-determiner
    that what whatever which whichever
WP: WH-pronoun
    that what whatever whatsoever which who whom whosoever
WP$: WH-pronoun, possessive
    whose
WRB: Wh-adverb
    how however whence whenever where whereby whereever wherein whereof why

Solution 3

The accepted answer above is missing the following information:

There are also 9 punctuation tags defined (which are not listed in some references, see here). These are:

1. #
2. $
3. '' (used for all forms of closing quote)
4. ( (used for all forms of opening parenthesis)
5. ) (used for all forms of closing parenthesis)
6. ,
7. . (used for all sentence-ending punctuation)
8. : (used for colons, semicolons and ellipses)
9. `` (used for all forms of opening quote)

Solution 4

Here is a more complete list of tags for the Penn Treebank (posted here for the sake of completness):

http://www.surdeanu.info/mihai/teaching/ista555-fall13/readings/PennTreebankConstituents.html

It also includes tags for clause and phrase levels.

Clause Level

- S
- SBAR
- SBARQ
- SINV
- SQ

Phrase Level

- ADJP
- ADVP
- CONJP
- FRAG
- INTJ
- LST
- NAC
- NP
- NX
- PP
- PRN
- PRT
- QP
- RRC
- UCP
- VP
- WHADJP
- WHAVP
- WHNP
- WHPP
- X

(descriptions in the link)

Solution 5

Codified:

/**
 * Represents the English parts-of-speech, encoded using the
 * de facto <a href="http://www.cis.upenn.edu/~treebank/">Penn Treebank
 * Project</a> standard.
 * 
 * @see <a href="ftp://ftp.cis.upenn.edu/pub/treebank/doc/tagguide.ps.gz">Penn Treebank Specification</a>
 */
public enum PartOfSpeech {
  ADJECTIVE( "JJ" ),
  ADJECTIVE_COMPARATIVE( ADJECTIVE + "R" ),
  ADJECTIVE_SUPERLATIVE( ADJECTIVE + "S" ),

  /* This category includes most words that end in -ly as well as degree
   * words like quite, too and very, posthead modi ers like enough and
   * indeed (as in good enough, very well indeed), and negative markers like
   * not, n't and never.
   */
  ADVERB( "RB" ),
  
  /* Adverbs with the comparative ending -er but without a strictly comparative
   * meaning, like <i>later</i> in <i>We can always come by later</i>, should
   * simply be tagged as RB.
   */
  ADVERB_COMPARATIVE( ADVERB + "R" ),
  ADVERB_SUPERLATIVE( ADVERB + "S" ),
  
  /* This category includes how, where, why, etc.
   */
  ADVERB_WH( "W" + ADVERB ),

  /* This category includes and, but, nor, or, yet (as in Y et it's cheap,
   * cheap yet good), as well as the mathematical operators plus, minus, less,
   * times (in the sense of "multiplied by") and over (in the sense of "divided
   * by"), when they are spelled out. <i>For</i> in the sense of "because" is
   * a coordinating conjunction (CC) rather than a subordinating conjunction.
   */
  CONJUNCTION_COORDINATING( "CC" ),
  CONJUNCTION_SUBORDINATING( "IN" ),
  CARDINAL_NUMBER( "CD" ),
  DETERMINER( "DT" ),
  
  /* This category includes which, as well as that when it is used as a
   * relative pronoun.
   */
  DETERMINER_WH( "W" + DETERMINER ),
  EXISTENTIAL_THERE( "EX" ),
  FOREIGN_WORD( "FW" ),

  LIST_ITEM_MARKER( "LS" ),
  
  NOUN( "NN" ),
  NOUN_PLURAL( NOUN + "S" ),
  NOUN_PROPER_SINGULAR( NOUN + "P" ),
  NOUN_PROPER_PLURAL( NOUN + "PS" ),

  PREDETERMINER( "PDT" ),
  POSSESSIVE_ENDING( "POS" ),

  PRONOUN_PERSONAL( "PRP" ),
  PRONOUN_POSSESSIVE( "PRP$" ),
  
  /* This category includes the wh-word whose.
   */
  PRONOUN_POSSESSIVE_WH( "WP$" ),
  
  /* This category includes what, who and whom.
   */
  PRONOUN_WH( "WP" ),

  PARTICLE( "RP" ),
  
  /* This tag should be used for mathematical, scientific and technical symbols
   * or expressions that aren't English words. It should not used for any and
   * all technical expressions. For instance, the names of chemicals, units of
   * measurements (including abbreviations thereof) and the like should be
   * tagged as nouns.
   */
  SYMBOL( "SYM" ),
  TO( "TO" ),
  
  /* This category includes my (as in M y, what a gorgeous day), oh, please,
   * see (as in See, it's like this), uh, well and yes, among others.
   */
  INTERJECTION( "UH" ),

  VERB( "VB" ),
  VERB_PAST_TENSE( VERB + "D" ),
  VERB_PARTICIPLE_PRESENT( VERB + "G" ),
  VERB_PARTICIPLE_PAST( VERB + "N" ),
  VERB_SINGULAR_PRESENT_NONTHIRD_PERSON( VERB + "P" ),
  VERB_SINGULAR_PRESENT_THIRD_PERSON( VERB + "Z" ),

  /* This category includes all verbs that don't take an -s ending in the
   * third person singular present: can, could, (dare), may, might, must,
   * ought, shall, should, will, would.
   */
  VERB_MODAL( "MD" ),

  /* Stanford.
   */
  SENTENCE_TERMINATOR( "." );

  private final String tag;

  private PartOfSpeech( String tag ) {
    this.tag = tag;
  }

  /**
   * Returns the encoding for this part-of-speech.
   * 
   * @return A string representing a Penn Treebank encoding for an English
   * part-of-speech.
   */
  public String toString() {
    return getTag();
  }
  
  protected String getTag() {
    return this.tag;
  }

  public static PartOfSpeech get( String value ) {
    for( PartOfSpeech v : values() ) {
      if( value.equals( v.getTag() ) ) {
        return v;
      }
    }
    
    throw new IllegalArgumentException( "Unknown part of speech: '" + value + "'." );
  }
}

View more solutions

Comments

[Joseph]

This may be a nitpick, but you should use .starts_with('N') rather than contains, since 'IN' and 'VBN' also contain 'N'. And that is probably the best way to find which words the tagger thinks are nouns.

[Christopher Manning]

No, they are Penn English Treebank POS tags, which are a simplification of the Brown Corpus tag set.

[Jules]

Are you sure? The example quoted above includes a tag of "." which is defined in the Brown Corpus, but isn't defined by the list of Penn Treebank tags above, so it seems fairly certain that at the very least the answer isn't as simple as they're just Penn Treebank tags.

[Jules]

My suggestion of an edit to fix a deficiency in this answer was rejected. Therefore, please also see my posted answer below which contains some information missing from this answer.

[Jules]

Having done additional research, it appears that they are Penn Treebank tags, but that the documentation quoted above on such tags is incomplete: Penn Treebank tags also include 9 punctuation mark tags that have been omitted from the list in the accepted answer. See my additional answer for more details.

[Devavrata]

What is 10th LS exactly ?

[quemeful]

"to" must be special. got its own tag

[CoolHandLouis]

A really great reference to this is Erwin R. Komen's List and Explanation of Parts of Speech Tags. Also of interest may be Komen's Research in English and Komen's homepage, erwinkomen.ruhosting.nl

[windweller]

You know what? This is the true list that people need! Not just the Penn Treebank POS tags because those are just for words

[David Portabella]

can you please cite the source?

[David Portabella]

what about the punctuations? for instance, a ',' token gets the PoS ','. is there a list that includes these PoS?

[David Portabella]

What about the PoS "-LRB-" for the '(' token?

[gokul_uf]

Are the tags used in Stanford POS Tagger and Penn Tree bank same?

[Kyordhel]

@gokul_uf No, they are not the exactly the same. The StanfordCoreNLP returns sometimes FRAG tags. Other I've found are -LRB- and -RRB- (square brackets) but one is enough to state that there is no 1:1 correlation.

[Petrus Theron]

Could you add the descriptions next to the abbreviations?

[Huluvu424242]

I am missing some tags for german: APPR, VVFIN see here: ims.uni-stuttgart.de/forschung/ressourcen/lexika/TagSets/…

[Catalina Chircu]

@AMArostegui : Thank you for the hint. Please share a link where it is expressely mentioned that the Universal dependencies are used for Spanish. The link is for the UD but there is not hint that they are actually used for Spanish in Stanfoird Core NLP and the official documentation of Stanford does not mention it neither.